How I Started Tracking My ML Experiments Like a Pro

Line 5: We import the mlflow library Line 6: Here, we import the relevant mlflow.sklearn This entirely depends on which package the model is built on. The complete list of available modules can be found in the official MLflow Python API documentation. Line 7: Autologging is a recently introduced experimental feature that makes the MLflow integration hassle-free. This function automatically logs all the parameters, metrics and saves the model artifacts in one place.